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AgglomerativeParams

Parameters for Agglomerative clustering algorithm.

Properties

Name Type Description Notes
n_clusters int Number of clusters to find. Can be None if distance_threshold is not None [optional] [default to 2]
affinity str Metric used to compute linkage. Can be 'euclidean', 'l1', 'l2', 'manhattan', 'cosine', or 'precomputed' [optional] [default to 'euclidean']
memory str Path to the caching directory [optional]
connectivity object [optional]
compute_full_tree str Whether to compute the full tree ('auto', True, or False) [optional] [default to 'auto']
linkage str Linkage criterion ('ward', 'complete', 'average', 'single') [optional] [default to 'ward']
distance_threshold float The linkage distance threshold above which clusters will not be merged [optional]
compute_distances bool Whether to compute distances between clusters [optional] [default to False]

Example

from mixpeek.models.agglomerative_params import AgglomerativeParams

# TODO update the JSON string below
json = "{}"
# create an instance of AgglomerativeParams from a JSON string
agglomerative_params_instance = AgglomerativeParams.from_json(json)
# print the JSON string representation of the object
print(AgglomerativeParams.to_json())

# convert the object into a dict
agglomerative_params_dict = agglomerative_params_instance.to_dict()
# create an instance of AgglomerativeParams from a dict
agglomerative_params_from_dict = AgglomerativeParams.from_dict(agglomerative_params_dict)

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